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Christian Weilbach
标题
引用次数
引用次数
年份
Flexible diffusion modeling of long videos
W Harvey, S Naderiparizi, V Masrani, C Weilbach, F Wood
Advances in Neural Information Processing Systems 35, 27953-27965, 2022
1962022
Structured conditional continuous normalizing flows for efficient amortized inference in graphical models
C Weilbach, B Beronov, F Wood, W Harvey
International Conference on Artificial Intelligence and Statistics, 4441-4451, 2020
212020
Planning as inference in epidemiological dynamics models
F Wood, A Warrington, S Naderiparizi, C Weilbach, V Masrani, W Harvey, ...
Frontiers in Artificial Intelligence 4, 550603, 2022
182022
Graphically structured diffusion models
CD Weilbach, W Harvey, F Wood
International Conference on Machine Learning, 36887-36909, 2023
52023
Inferring the structure of ordinary differential equations
J Weilbach, S Gerwinn, C Weilbach, M Kandemir
arXiv preprint arXiv:2107.07345, 2021
52021
All-in-one simulation-based inference
M Gloeckler, M Deistler, C Weilbach, F Wood, JH Macke
arXiv preprint arXiv:2404.09636, 2024
32024
If the sources could talk: Evaluating large language models for research assistance in history
GG Garcia, C Weilbach
arXiv preprint arXiv:2310.10808, 2023
32023
Decoupling conflicts for configurable resolution in an open replication system
C Weilbach, K Kühne, A Bieniusa
arXiv preprint arXiv:1508.05545, 2015
32015
Trans-dimensional generative modeling via jump diffusion models
A Campbell, W Harvey, C Weilbach, V De Bortoli, T Rainforth, A Doucet
Advances in Neural Information Processing Systems 36, 2024
22024
Efficient inference amortization in graphical models using structured continuous conditional normalizing flows
C Weilbach, B Beronov, W Harvey, F Wood
Second Symposium on Advances in Approximate Bayesian Inference, 2019
22019
Sequential Core-Set Monte Carlo
B Beronov, C Weilbach, F Wood, T Campbell
Uncertainty in Artificial Intelligence, 2165-2175, 2021
12021
Decoupling conflict resolution with CDVCS
C Weilbach, K Kühne, A Bieniusa
Proceedings of the 2nd Workshop on the Principles and Practice of …, 2016
12016
replikativ. io: Composable consistency primitives for a scalable and robust global replication system.
C Weilbach, K Kühne, A Bieniusa
CoRR, 2015
12015
Prospective Messaging: Learning in Networks with Communication Delays
R Fayyazi, C Weilbach, F Wood
arXiv preprint arXiv:2407.05494, 2024
2024
Scaling Graphically Structured Diffusion Models
CD Weilbach, W Harvey, H Shirzad, F Wood
ICML 2023 Workshop on Structured Probabilistic Inference {\&} Generative …, 2023
2023
Useful Uncertainties in Reinforcement Learning
C Weilbach
2018
Techreport: Time-sensitive probabilistic inference for the edge
C Weilbach, A Bieniusa
arXiv preprint arXiv:1710.11057, 2017
2017
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